Bayesian transition models for ordinal longitudinal outcomes

DOI10.1002/sim.10133zbMath1545.62523MaRDI QIDQ6618362

Maximilian D. Rohde, Thomas G. Stewart, Frank E. jun. Harrell, Benjamin French

Publication date: 14 October 2024

Published in: Statistics in Medicine (Search for Journal in Brave)

zbMATH Keywords

clinical trialsBayesian modelingtransition modelsordinal longitudinal outcomes

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Cites Work

• Longitudinal data analysis using generalized linear models
• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• Random-Effects Models for Longitudinal Data
• Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis
• Rank-normalization, folding, and localization: an improved \(\widehat{R}\) for assessing convergence of MCMC (with Discussion)
• On the Theory of Scales of Measurement
• Ordinal Measures of Association
• Estimating time-to-event from longitudinal ordinal data using random-effects Markov models: application to multiple sclerosis progression
• Longitudinal analysis of repeated binary data using autoregressive and random effect modelling
• Sampling-Based Approaches to Calculating Marginal Densities
• Partial Proportional Odds Models for Ordinal Response Variables
• Handbook of Markov Chain Monte Carlo
• Estimating Time to Disease Progression Comparing Transition Models and Survival Methods—An Analysis of Multiple Sclerosis Data
• Linear and Generalized Linear Models and their Applications by J. JIANG
• Ordinal regression: a review and a taxonomy of models
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Bayesian transition models for ordinal longitudinal outcomes